Sustained performance of knowledge-based potentials in fold recognition.

We describe the results obtained using fold recognition techniques in our third participation in the CASP experiment. The approach relies on knowledge-based potentials for alignment production and fold identification. As indicated by the increase in alignment quality and fold identification reliability, the predictions improved from CASP1 to CASP3. In particular, we identified structural relationships in which no known evolutionary link exists. Our predictions are based on single sequences rather than multiple sequence alignments. Additionally, we voluntarily submitted only a single model for each target because, in our view, submission of a single model is the most stringent test. We describe the methods used, the strategy adopted in the predictions, and the prediction results and discuss future work.